FastAPI service that turns text into embedding vectors using Qwen3-Embedding-0.6B (GGUF quantized) via llama-cpp-python, designed for the ICICLE AI Tapis tenant. The service runs the model locally — no external API calls — so a single .gguf file plus a Tapis token is everything a deployment needs.
FastAPI + Qdrant vector storage and retrieval service for the ICICLE AI Tapis tenant. Clients provide their own pre-computed embeddings — the service handles storage, search, and reranking.
An interactive marimo notebook that turns the ICICLE AI Tapis services into a hands-on RAG (retrieval-augmented generation) playground. Paste any text, ingest it into the vector store, and chat against it — the notebook chains the embed, vector, and chat services behind a single Tapis access token.
A 7-step HPC-backed pipeline for few-shot object detection — from interactive image annotation through class support generation, proposal visualization, and Tapis-powered job execution — built to work across any research domain.